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Herrero-Garcia, J., Schwetz, T., & Zupan, J. (2012). On the annual modulation signal in dark matter direct detection. J. Cosmol. Astropart. Phys., 03(3), 005–28pp.
Abstract: We derive constraints on the annual modulation signal in Dark Matter (DM) direct detection experiments in terms of the unmodulated event rate. A general bound independent of the details of the DM distribution follows from the assumption that the motion of the earth around the sun is the only source of time variation. The bound is valid for a very general class of particle physics models and also holds in the presence of an unknown unmodulated background. More stringent bounds are obtained, if modest assumptions on symmetry properties of the DM halo are adopted. We illustrate the bounds by applying them to the annual modulation signals reported by the DAMA and CoGeNT experiments in the framework of spin-independent elastic scattering. While the DAMA signal satisfies our bounds, severe restrictions on the DM mass can be set for CoGeNT.
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Herrero-Garcia, J., Schwetz, T., & Zupan, J. (2012). Astrophysics independent bounds on the annual modulation of dark matter signals. Phys. Rev. Lett., 109(14), 141301–5pp.
Abstract: We show how constraints on the time integrated event rate from a given dark matter (DM) direct detection experiment can be used to bound the amplitude of the annual modulation signal in another experiment. The method requires only mild assumptions about the properties of the local DM distribution: that it is temporally stable on the scale of months and spatially homogeneous on the ecliptic. We apply the method to the annual modulation signal in DAMA/LIBRA, which we compare to the bounds derived from XENON10, XENON100, cryogenic DM search, and SIMPLE data. Assuming a DM mass of 10 GeV, we show that under the above assumptions about the DM halo, a DM interpretation of the DAMA/LIBRA signal is excluded for several classes of models: at 6.3 sigma (4.6 sigma) for elastic isospin conserving (violating) spin-independent interactions, and at 4.9 sigma for elastic spin-dependent interactions on protons.
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Herrero-Garcia, J., Rius, N., & Santamaria, A. (2016). Higgs lepton flavour violation: UV completions and connection to neutrino masses. J. High Energy Phys., 11(11), 084–45pp.
Abstract: We study lepton violating Higgs (HLFV) decays, first from the effective field theory (EFT) point of view, and then analysing the different high-energy realizations of the operators of the EFT, highlighting the most promising models. We argue why two Higgs doublet models can have a BR(h -> tau mu) similar to 0:01, and why this rate is suppressed in all other realizations including vector-like leptons. We further discuss HLFV in the context of neutrino mass models: in most cases it is generated at one loop giving always BR (h -> tau mu) < 10(-4) and typically much less, which is beyond experimental reach. However, both the Zee model and extended left-right symmetric models contain extra SU(2) doublets coupled to leptons and could in principle account for the observed excess, with interesting connections between HLFV and neutrino parameters.
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Herrero-Garcia, J., Patrick, R., & Scaffidi, A. (2022). A semi-supervised approach to dark matter searches in direct detection data with machine learning. J. Cosmol. Astropart. Phys., 02, 039–19pp.
Abstract: The dark matter sector remains completely unknown. It is therefore crucial to keep an open mind regarding its nature and possible interactions. Focusing on the case of Weakly Interacting Massive Particles, in this work we make this general philosophy more concrete by applying modern machine learning techniques to dark matter direct detection. We do this by encoding and decoding the graphical representation of background events in the XENONnT experiment with a convolutional variational autoencoder. We describe a methodology that utilizes the `anomaly score' derived from the reconstruction loss of the convolutional variational autoencoder as well as a pre-trained standard convolutional neural network, in a semi-supervised fashion. Indeed, we observe that optimum results are obtained only when both unsupervised and supervised anomaly scores are considered together. A data set that has a higher proportion of anomaly score is deemed anomalous and deserves further investigation. Contrary to classical analyses, in principle all information about the events is used, preventing unnecessary information loss. Lastly, we demonstrate the reach of learning-focused anomaly detection in this context by comparing results with classical inference, observing that, if tuned properly, these techniques have the potential to outperform likelihood-based methods.
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Herrero-Garcia, J., Nebot, M., Rius, N., & Santamaria, A. (2014). The Zee-Babu model revisited in the light of new data. Nucl. Phys. B, 885, 542–570.
Abstract: We update previous analyses of the Zee-Babu model in the light of new data, e.g., the mixing angle On, the rare decay μ-> e gamma and the LHC results. We also analyze the possibility of accommodating the deviations in Gamma (H -> gamma gamma) hinted by the LHC experiments, and the stability of the scalar potential. We find that neutrino oscillation data and low energy constraints are still compatible with masses of the extra charged scalars accessible to LHC. Moreover, if any of them is discovered, the model can be falsified by combining the information on the singly and doubly charged scalar decay modes with neutrino data. Conversely, if the neutrino spectrum is found to be inverted and the CP phase delta is quite different from pi, the masses of the charged scalars will be well outside the LHC reach.
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